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About

Phan Xuan Minh is a robotics researcher whose work focuses on advancing the control and estimation algorithms for mobile robots and robotic manipulators. His primary research areas include trajectory tracking control, sliding mode control, and sensor data fusion for robotic systems. Minh’s most significant contribution is the development of a novel backstepping hierarchical sliding mode tracking control algorithm for wheeled mobile robots, published in 2019 and cited 21 times. This work integrates hierarchical sliding mode and backstepping techniques to guarantee closed-loop stability and precise trajectory tracking, addressing a critical challenge in autonomous navigation. He has also contributed to dynamic surface control for four-wheel differential drive mobile robots, accounting for wheel slip—a practical issue in real-world applications. Additionally, Minh has developed adaptive Kalman filters for fusing IMU and encoder data to estimate acceleration in robot arms, enhancing sensor accuracy in noisy environments. His research, though early in its citation impact, demonstrates a clear trajectory toward solving fundamental problems in robot mobility and sensing, making him a promising figure in the field of intelligent robotics.